Triple
T2057500
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | Berkeley College White Plains campus |
E45707
|
entity |
| Predicate | offersProgramInField |
P2581
|
FINISHED |
| Object | business |
—
|
LITERAL FINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: business | Statement: [Berkeley College White Plains campus, offersProgramInField, business]
PD
Predicate disambiguation
gpt-5-mini-2025-08-07
Target predicate: offersProgramInField Context triple: [Berkeley College White Plains campus, offersProgramInField, business]
-
A.
offersProgram
Indicates that an entity provides or makes available a specific program (such as a course, curriculum, or initiative).
-
B.
offersProgramLevel
Indicates that an entity provides or makes available an academic or training program at a specified level (e.g., undergraduate, graduate, certificate).
-
C.
offersProgramsIn
chosen
Indicates that an institution or provider makes educational or training programs available in a particular field, subject, or area.
-
D.
offersFeature
Indicates that one entity provides or makes available a particular feature or capability to another entity.
-
E.
offersActivity
Indicates that one entity provides or makes available a specific activity for another entity to participate in or use.
- F. None of above.
Provenance (3 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69a8891a19508190a12ef1e192308dcb |
completed | March 4, 2026, 7:33 p.m. |
| NER | Named-entity recognition | batch_69abb9ae0130819089f7d62005466a45 |
completed | March 7, 2026, 5:37 a.m. |
| PD | Predicate disambiguation | batch_69abb7ad5a7c8190b92575d6053b3fb7 |
completed | March 7, 2026, 5:29 a.m. |
Created at: March 4, 2026, 7:40 p.m.